time
(num_lines)
float64
dask.array<chunksize=(9868,), meta=np.ndarray>

- long_name :
-
time in UTC
- standard_name :
-
time
- calendar :
-
gregorian
- leap_second :
-
YYYY-MM-DDThh:mm:ssZ
- units :
-
seconds since 2000-01-01 00:00:00.0
- comment :
-
Time of measurement in seconds in the UTC time scale since 1 Jan 2000 00:00:00 UTC. [tai_utc_difference] is the difference between TAI and UTC reference time (seconds) for the first measurement of the data set. If a leap second occurs within the data set, the attribute leap_second is set to the UTC time at which the leap second occurs.
- tai_utc_difference :
-
35.0
| Bytes |
2.18 MiB |
77.09 kiB |
| Shape |
(286144,) |
(9868,) |
| Dask graph |
29 chunks in 59 graph layers |
| Data type |
float64 numpy.ndarray |
|
 |
time_tai
(num_lines)
float64
dask.array<chunksize=(9868,), meta=np.ndarray>

- long_name :
-
time in TAI
- standard_name :
-
time
- calendar :
-
gregorian
- tai_utc_difference :
-
[Value of TAI-UTC at time of first record]
- units :
-
seconds since 2000-01-01 00:00:00.0
- comment :
-
Time of measurement in seconds in the TAI time scale since 1 Jan 2000 00:00:00 TAI. This time scale contains no leap seconds. The difference (in seconds) with time in UTC is given by the attribute [time:tai_utc_difference].
| Bytes |
2.18 MiB |
77.09 kiB |
| Shape |
(286144,) |
(9868,) |
| Dask graph |
29 chunks in 59 graph layers |
| Data type |
float64 numpy.ndarray |
|
 |
ssh_karin
(num_lines, num_pixels)
float64
dask.array<chunksize=(9868, 71), meta=np.ndarray>

- long_name :
-
sea surface height
- standard_name :
-
sea surface height above reference ellipsoid
- units :
-
m
- valid_min :
-
-15000000
- valid_max :
-
150000000
- comment :
-
Fully corrected sea surface height measured by KaRIn. The height is relative to the reference ellipsoid defined in the global attributes. This value is computed using radiometer measurements for wet troposphere effects on the KaRIn measurement (e.g., rad_wet_tropo_cor and sea_state_bias_cor).
| Bytes |
155.00 MiB |
5.35 MiB |
| Shape |
(286144, 71) |
(9868, 71) |
| Dask graph |
29 chunks in 59 graph layers |
| Data type |
float64 numpy.ndarray |
|
 |
ssh_karin_uncert
(num_lines, num_pixels)
float32
dask.array<chunksize=(9868, 71), meta=np.ndarray>

- long_name :
-
sea surface height anomaly uncertainty
- units :
-
m
- valid_min :
-
0
- valid_max :
-
60000
- comment :
-
1-sigma uncertainty on the sea surface height from the KaRIn measurement.
| Bytes |
77.50 MiB |
2.67 MiB |
| Shape |
(286144, 71) |
(9868, 71) |
| Dask graph |
29 chunks in 59 graph layers |
| Data type |
float32 numpy.ndarray |
|
 |
ssha_karin
(num_lines, num_pixels)
float64
dask.array<chunksize=(9868, 71), meta=np.ndarray>

- long_name :
-
sea surface height anomaly
- units :
-
m
- valid_min :
-
-1000000
- valid_max :
-
1000000
- comment :
-
Sea surface height anomaly from the KaRIn measurement = ssh_karin - mean_sea_surface_cnescls - solid_earth_tide - ocean_tide_fes – internal_tide_hret - pole_tide - dac.
| Bytes |
155.00 MiB |
5.35 MiB |
| Shape |
(286144, 71) |
(9868, 71) |
| Dask graph |
29 chunks in 59 graph layers |
| Data type |
float64 numpy.ndarray |
|
 |
ssh_karin_2
(num_lines, num_pixels)
float64
dask.array<chunksize=(9868, 71), meta=np.ndarray>

- long_name :
-
sea surface height
- standard_name :
-
sea surface height above reference ellipsoid
- units :
-
m
- valid_min :
-
-15000000
- valid_max :
-
150000000
- comment :
-
Fully corrected sea surface height measured by KaRIn. The height is relative to the reference ellipsoid defined in the global attributes. This value is computed using model-based estimates for wet troposphere effects on the KaRIn measurement (e.g., model_wet_tropo_cor and sea_state_bias_cor_2).
| Bytes |
155.00 MiB |
5.35 MiB |
| Shape |
(286144, 71) |
(9868, 71) |
| Dask graph |
29 chunks in 59 graph layers |
| Data type |
float64 numpy.ndarray |
|
 |
ssha_karin_2
(num_lines, num_pixels)
float64
dask.array<chunksize=(9868, 71), meta=np.ndarray>

- long_name :
-
sea surface height anomaly
- units :
-
m
- valid_min :
-
-1000000
- valid_max :
-
1000000
- comment :
-
Sea surface height anomaly from the KaRIn measurement = ssh_karin_2 - mean_sea_surface_cnescls - solid_earth_tide - ocean_tide_fes – internal_tide_hret - pole_tide - dac.
| Bytes |
155.00 MiB |
5.35 MiB |
| Shape |
(286144, 71) |
(9868, 71) |
| Dask graph |
29 chunks in 59 graph layers |
| Data type |
float64 numpy.ndarray |
|
 |
ssha_karin_qual
(num_lines, num_pixels)
float64
dask.array<chunksize=(9868, 71), meta=np.ndarray>

- long_name :
-
sea surface height quality flag
- standard_name :
-
status_flag
- flag_meanings :
-
good bad
- flag_values :
-
[0 1]
- valid_min :
-
0
- valid_max :
-
1
- comment :
-
Quality flag for the SSHA from KaRIn.
| Bytes |
155.00 MiB |
5.35 MiB |
| Shape |
(286144, 71) |
(9868, 71) |
| Dask graph |
29 chunks in 59 graph layers |
| Data type |
float64 numpy.ndarray |
|
 |
polarization_karin
(num_lines, num_sides)
object
dask.array<chunksize=(9868, 2), meta=np.ndarray>

- long_name :
-
polarization for each side of the KaRIn swath
- comment :
-
H denotes co-polarized linear horizontal, V denotes co-polarized linear vertical.
| Bytes |
4.37 MiB |
154.19 kiB |
| Shape |
(286144, 2) |
(9868, 2) |
| Dask graph |
29 chunks in 59 graph layers |
| Data type |
object numpy.ndarray |
|
 |
swh_karin
(num_lines, num_pixels)
float32
dask.array<chunksize=(9868, 71), meta=np.ndarray>

- long_name :
-
significant wave height from KaRIn
- standard_name :
-
sea_surface_wave_significant_height
- units :
-
m
- valid_min :
-
0
- valid_max :
-
25000
- comment :
-
Significant wave height from KaRIn volumetric correlation.
| Bytes |
77.50 MiB |
2.67 MiB |
| Shape |
(286144, 71) |
(9868, 71) |
| Dask graph |
29 chunks in 59 graph layers |
| Data type |
float32 numpy.ndarray |
|
 |
swh_karin_uncert
(num_lines, num_pixels)
float32
dask.array<chunksize=(9868, 71), meta=np.ndarray>

- long_name :
-
1-sigma uncertainty on significant wave height from KaRIn
- units :
-
m
- valid_min :
-
0
- valid_max :
-
25000
- comment :
-
1-sigma uncertainty on significant wave height from KaRIn.
| Bytes |
77.50 MiB |
2.67 MiB |
| Shape |
(286144, 71) |
(9868, 71) |
| Dask graph |
29 chunks in 59 graph layers |
| Data type |
float32 numpy.ndarray |
|
 |
sig0_karin
(num_lines, num_pixels)
float32
dask.array<chunksize=(9868, 71), meta=np.ndarray>

- long_name :
-
normalized radar cross section (sigma0) from KaRIn
- standard_name :
-
surface_backwards_scattering_coefficient_of_radar_wave
- units :
-
1
- valid_min :
-
-1000.0
- valid_max :
-
10000000.0
- comment :
-
Normalized radar cross section (sigma0) from KaRIn in real, linear units (not decibels). The value may be negative due to noise subtraction. The value is corrected for instrument calibration and atmospheric attenuation. Radiometer measurements provide the atmospheric attenuation (sig0_cor_atmos_rad).
| Bytes |
77.50 MiB |
2.67 MiB |
| Shape |
(286144, 71) |
(9868, 71) |
| Dask graph |
29 chunks in 59 graph layers |
| Data type |
float32 numpy.ndarray |
|
 |
sig0_karin_uncert
(num_lines, num_pixels)
float32
dask.array<chunksize=(9868, 71), meta=np.ndarray>

- long_name :
-
1-sigma uncertainty on sigma0 from KaRIn
- units :
-
1
- valid_min :
-
0.0
- valid_max :
-
1000.0
- comment :
-
1-sigma uncertainty on sigma0 from KaRIn.
| Bytes |
77.50 MiB |
2.67 MiB |
| Shape |
(286144, 71) |
(9868, 71) |
| Dask graph |
29 chunks in 59 graph layers |
| Data type |
float32 numpy.ndarray |
|
 |
sig0_karin_2
(num_lines, num_pixels)
float32
dask.array<chunksize=(9868, 71), meta=np.ndarray>

- long_name :
-
normalized radar cross section (sigma0) from KaRIn
- standard_name :
-
surface_backwards_scattering_coefficient_of_radar_wave
- units :
-
1
- valid_min :
-
-1000.0
- valid_max :
-
10000000.0
- comment :
-
Normalized radar cross section (sigma0) from KaRIn in real, linear units (not decibels). The value may be negative due to noise subtraction. The value is corrected for instrument calibration and atmospheric attenuation. A meteorological model provides the atmospheric attenuation (sig0_cor_atmos_model).
| Bytes |
77.50 MiB |
2.67 MiB |
| Shape |
(286144, 71) |
(9868, 71) |
| Dask graph |
29 chunks in 59 graph layers |
| Data type |
float32 numpy.ndarray |
|
 |
wind_speed_karin
(num_lines, num_pixels)
float32
dask.array<chunksize=(9868, 71), meta=np.ndarray>

- long_name :
-
wind speed from KaRIn
- standard_name :
-
wind_speed
- source :
-
TBD
- units :
-
m/s
- valid_min :
-
0
- valid_max :
-
65000
- comment :
-
Wind speed from KaRIn computed from sig0_karin.
| Bytes |
77.50 MiB |
2.67 MiB |
| Shape |
(286144, 71) |
(9868, 71) |
| Dask graph |
29 chunks in 59 graph layers |
| Data type |
float32 numpy.ndarray |
|
 |
wind_speed_karin_2
(num_lines, num_pixels)
float32
dask.array<chunksize=(9868, 71), meta=np.ndarray>

- long_name :
-
wind speed from KaRIn
- standard_name :
-
wind_speed
- source :
-
TBD
- units :
-
m/s
- valid_min :
-
0
- valid_max :
-
65000
- comment :
-
Wind speed from KaRIn computed from sig0_karin_2.
| Bytes |
77.50 MiB |
2.67 MiB |
| Shape |
(286144, 71) |
(9868, 71) |
| Dask graph |
29 chunks in 59 graph layers |
| Data type |
float32 numpy.ndarray |
|
 |
swh_karin_qual
(num_lines, num_pixels)
float64
dask.array<chunksize=(9868, 71), meta=np.ndarray>

- long_name :
-
quality flag for significant wave height from KaRIn.
- standard_name :
-
status_flag
- flag_meanings :
-
good bad
- flag_values :
-
[0 1]
- valid_min :
-
0
- valid_max :
-
1
- comment :
-
Quality flag for significant wave height from KaRIn.
| Bytes |
155.00 MiB |
5.35 MiB |
| Shape |
(286144, 71) |
(9868, 71) |
| Dask graph |
29 chunks in 59 graph layers |
| Data type |
float64 numpy.ndarray |
|
 |
sig0_karin_qual
(num_lines, num_pixels)
float64
dask.array<chunksize=(9868, 71), meta=np.ndarray>

- long_name :
-
quality flag for sigma0 from KaRIn.
- standard_name :
-
status_flag
- flag_meanings :
-
good bad
- flag_values :
-
[0 1]
- valid_min :
-
0
- valid_max :
-
1
- comment :
-
Quality flag for sigma0 from KaRIn.
| Bytes |
155.00 MiB |
5.35 MiB |
| Shape |
(286144, 71) |
(9868, 71) |
| Dask graph |
29 chunks in 59 graph layers |
| Data type |
float64 numpy.ndarray |
|
 |
num_pt_avg
(num_lines, num_pixels)
float32
dask.array<chunksize=(9868, 71), meta=np.ndarray>

- long_name :
-
number of samples averaged
- units :
-
1
- valid_min :
-
0
- valid_max :
-
289
- comment :
-
Number of native unsmoothed, beam-combined KaRIn samples averaged.
| Bytes |
77.50 MiB |
2.67 MiB |
| Shape |
(286144, 71) |
(9868, 71) |
| Dask graph |
29 chunks in 59 graph layers |
| Data type |
float32 numpy.ndarray |
|
 |
swh_model
(num_lines, num_pixels)
float32
dask.array<chunksize=(9868, 71), meta=np.ndarray>

- long_name :
-
significant wave height from wave model
- standard_name :
-
sea_surface_wave_significant_height
- source :
-
European Centre for Medium-Range Weather Forecasts
- institution :
-
ECMWF
- units :
-
m
- valid_min :
-
0
- valid_max :
-
30000
- comment :
-
Significant wave height from model.
| Bytes |
77.50 MiB |
2.67 MiB |
| Shape |
(286144, 71) |
(9868, 71) |
| Dask graph |
29 chunks in 59 graph layers |
| Data type |
float32 numpy.ndarray |
|
 |
mean_wave_direction
(num_lines, num_pixels)
float32
dask.array<chunksize=(9868, 71), meta=np.ndarray>

- long_name :
-
mean sea surface wave direction
- source :
-
Meteo France Wave Model (MF-WAM)
- institution :
-
Meteo France
- units :
-
degree
- valid_min :
-
0
- valid_max :
-
36000
- comment :
-
Mean sea surface wave direction.
| Bytes |
77.50 MiB |
2.67 MiB |
| Shape |
(286144, 71) |
(9868, 71) |
| Dask graph |
29 chunks in 59 graph layers |
| Data type |
float32 numpy.ndarray |
|
 |
mean_wave_period_t02
(num_lines, num_pixels)
float32
dask.array<chunksize=(9868, 71), meta=np.ndarray>

- long_name :
-
sea surface wind wave mean period
- standard_name :
-
sea_surface_wave_significant_period
- source :
-
Meteo France Wave Model (MF-WAM)
- institution :
-
Meteo France
- units :
-
s
- valid_min :
-
0
- valid_max :
-
100
- comment :
-
Sea surface wind wave mean period from model spectral density second moment.
| Bytes |
77.50 MiB |
2.67 MiB |
| Shape |
(286144, 71) |
(9868, 71) |
| Dask graph |
29 chunks in 59 graph layers |
| Data type |
float32 numpy.ndarray |
|
 |
wind_speed_model_u
(num_lines, num_pixels)
float32
dask.array<chunksize=(9868, 71), meta=np.ndarray>

- long_name :
-
u component of model wind
- standard_name :
-
eastward_wind
- source :
-
European Centre for Medium-Range Weather Forecasts
- institution :
-
ECMWF
- units :
-
m/s
- valid_min :
-
-30000
- valid_max :
-
30000
- comment :
-
Eastward component of the atmospheric model wind vector at 10 meters.
| Bytes |
77.50 MiB |
2.67 MiB |
| Shape |
(286144, 71) |
(9868, 71) |
| Dask graph |
29 chunks in 59 graph layers |
| Data type |
float32 numpy.ndarray |
|
 |
wind_speed_model_v
(num_lines, num_pixels)
float32
dask.array<chunksize=(9868, 71), meta=np.ndarray>

- long_name :
-
v component of model wind
- standard_name :
-
northward_wind
- source :
-
European Centre for Medium-Range Weather Forecasts
- institution :
-
ECMWF
- units :
-
m/s
- valid_min :
-
-30000
- valid_max :
-
30000
- comment :
-
Northward component of the atmospheric model wind vector at 10 meters.
| Bytes |
77.50 MiB |
2.67 MiB |
| Shape |
(286144, 71) |
(9868, 71) |
| Dask graph |
29 chunks in 59 graph layers |
| Data type |
float32 numpy.ndarray |
|
 |
wind_speed_rad
(num_lines, num_sides)
float32
dask.array<chunksize=(9868, 2), meta=np.ndarray>

- long_name :
-
wind speed from radiometer
- standard_name :
-
wind_speed
- source :
-
Advanced Microwave Radiometer
- units :
-
m/s
- valid_min :
-
0
- valid_max :
-
65000
- comment :
-
Wind speed from radiometer measurements.
| Bytes |
2.18 MiB |
77.09 kiB |
| Shape |
(286144, 2) |
(9868, 2) |
| Dask graph |
29 chunks in 59 graph layers |
| Data type |
float32 numpy.ndarray |
|
 |
distance_to_coast
(num_lines, num_pixels)
float32
dask.array<chunksize=(9868, 71), meta=np.ndarray>

- long_name :
-
distance to coast
- source :
-
MODIS/GlobCover
- institution :
-
European Space Agency
- units :
-
m
- valid_min :
-
0
- valid_max :
-
21000
- comment :
-
Approximate distance to the nearest coast point along the Earth surface.
| Bytes |
77.50 MiB |
2.67 MiB |
| Shape |
(286144, 71) |
(9868, 71) |
| Dask graph |
29 chunks in 59 graph layers |
| Data type |
float32 numpy.ndarray |
|
 |
heading_to_coast
(num_lines, num_pixels)
float32
dask.array<chunksize=(9868, 71), meta=np.ndarray>

- long_name :
-
heading to coast
- units :
-
degrees
- valid_min :
-
0
- valid_max :
-
35999
- comment :
-
Approximate compass heading (0-360 degrees with respect to true north) to the nearest coast point.
| Bytes |
77.50 MiB |
2.67 MiB |
| Shape |
(286144, 71) |
(9868, 71) |
| Dask graph |
29 chunks in 59 graph layers |
| Data type |
float32 numpy.ndarray |
|
 |
ancillary_surface_classification_flag
(num_lines, num_pixels)
float32
dask.array<chunksize=(9868, 71), meta=np.ndarray>

- long_name :
-
surface classification
- standard_name :
-
status_flag
- source :
-
MODIS/GlobCover
- institution :
-
European Space Agency
- flag_meanings :
-
open_ocean land continental_water aquatic_vegetation continental_ice_snow floating_ice salted_basin
- flag_values :
-
[0 1 2 3 4 5 6]
- valid_min :
-
0
- valid_max :
-
6
- comment :
-
7-state surface type classification computed from a mask built with MODIS and GlobCover data.
| Bytes |
77.50 MiB |
2.67 MiB |
| Shape |
(286144, 71) |
(9868, 71) |
| Dask graph |
29 chunks in 59 graph layers |
| Data type |
float32 numpy.ndarray |
|
 |
dynamic_ice_flag
(num_lines, num_pixels)
float32
dask.array<chunksize=(9868, 71), meta=np.ndarray>

- long_name :
-
dynamic ice flag
- standard_name :
-
status_flag
- source :
-
EUMETSAT Ocean and Sea Ice Satellite Applications Facility
- institution :
-
EUMETSAT
- flag_meanings :
-
no_ice probable_ice ice
- flag_values :
-
[0 1 2]
- valid_min :
-
0
- valid_max :
-
2
- comment :
-
Dynamic ice flag for the location of the KaRIn measurement.
| Bytes |
77.50 MiB |
2.67 MiB |
| Shape |
(286144, 71) |
(9868, 71) |
| Dask graph |
29 chunks in 59 graph layers |
| Data type |
float32 numpy.ndarray |
|
 |
rain_flag
(num_lines, num_pixels)
float32
dask.array<chunksize=(9868, 71), meta=np.ndarray>

- long_name :
-
rain flag
- standard_name :
-
status_flag
- flag_meanings :
-
no_rain probable_rain rain
- flag_values :
-
[0 1 2]
- valid_min :
-
0
- valid_max :
-
2
- comment :
-
Flag indicates that signal is attenuated, probably from rain.
| Bytes |
77.50 MiB |
2.67 MiB |
| Shape |
(286144, 71) |
(9868, 71) |
| Dask graph |
29 chunks in 59 graph layers |
| Data type |
float32 numpy.ndarray |
|
 |
rad_surface_type_flag
(num_lines, num_sides)
float32
dask.array<chunksize=(9868, 2), meta=np.ndarray>

- long_name :
-
radiometer surface type flag
- standard_name :
-
status_flag
- source :
-
Advanced Microwave Radiometer
- flag_meanings :
-
open_ocean coastal_ocean land
- flag_values :
-
[0 1 2]
- valid_min :
-
0
- valid_max :
-
2
- comment :
-
Flag indicating the validity and type of processing applied to generate the wet troposphere correction (rad_wet_tropo_cor). A value of 0 indicates that open ocean processing is used, a value of 1 indicates coastal processing, and a value of 2 indicates that rad_wet_tropo_cor is invalid due to land contamination.
| Bytes |
2.18 MiB |
77.09 kiB |
| Shape |
(286144, 2) |
(9868, 2) |
| Dask graph |
29 chunks in 59 graph layers |
| Data type |
float32 numpy.ndarray |
|
 |
sc_altitude
(num_lines)
float64
dask.array<chunksize=(9868,), meta=np.ndarray>

- long_name :
-
altitude of KMSF origin
- standard_name :
-
height_above_reference_ellipsoid
- units :
-
m
- valid_min :
-
0
- valid_max :
-
2000000000
- comment :
-
Altitude of the KMSF origin.
| Bytes |
2.18 MiB |
77.09 kiB |
| Shape |
(286144,) |
(9868,) |
| Dask graph |
29 chunks in 59 graph layers |
| Data type |
float64 numpy.ndarray |
|
 |
orbit_alt_rate
(num_lines)
float32
dask.array<chunksize=(9868,), meta=np.ndarray>

- long_name :
-
orbital altitude rate with respect to mean sea surface
- units :
-
m/s
- valid_min :
-
-3500
- valid_max :
-
3500
- comment :
-
Orbital altitude rate with respect to the mean sea surface.
| Bytes |
1.09 MiB |
38.55 kiB |
| Shape |
(286144,) |
(9868,) |
| Dask graph |
29 chunks in 59 graph layers |
| Data type |
float32 numpy.ndarray |
|
 |
cross_track_angle
(num_lines)
float64
dask.array<chunksize=(9868,), meta=np.ndarray>

- long_name :
-
cross-track angle from true north
- units :
-
degrees
- valid_min :
-
0
- valid_max :
-
359999999
- comment :
-
Angle with respect to true north of the cross-track direction to the right of the spacecraft velocity vector.
| Bytes |
2.18 MiB |
77.09 kiB |
| Shape |
(286144,) |
(9868,) |
| Dask graph |
29 chunks in 59 graph layers |
| Data type |
float64 numpy.ndarray |
|
 |
sc_roll
(num_lines)
float64
dask.array<chunksize=(9868,), meta=np.ndarray>

- long_name :
-
roll of the spacecraft
- standard_name :
-
platform_roll_angle
- units :
-
degrees
- valid_min :
-
-1799999
- valid_max :
-
1800000
- comment :
-
KMSF attitude roll angle; positive values move the +y antenna down.
| Bytes |
2.18 MiB |
77.09 kiB |
| Shape |
(286144,) |
(9868,) |
| Dask graph |
29 chunks in 59 graph layers |
| Data type |
float64 numpy.ndarray |
|
 |
sc_pitch
(num_lines)
float64
dask.array<chunksize=(9868,), meta=np.ndarray>

- long_name :
-
pitch of the spacecraft
- standard_name :
-
platform_pitch_angle
- units :
-
degrees
- valid_min :
-
-1799999
- valid_max :
-
1800000
- comment :
-
KMSF attitude pitch angle; positive values move the KMSF +x axis up.
| Bytes |
2.18 MiB |
77.09 kiB |
| Shape |
(286144,) |
(9868,) |
| Dask graph |
29 chunks in 59 graph layers |
| Data type |
float64 numpy.ndarray |
|
 |
sc_yaw
(num_lines)
float64
dask.array<chunksize=(9868,), meta=np.ndarray>

- long_name :
-
yaw of the spacecraft
- standard_name :
-
platform_yaw_angle
- units :
-
degrees
- valid_min :
-
-1799999
- valid_max :
-
1800000
- comment :
-
KMSF attitude yaw angle relative to the nadir track. The yaw angle is a right-handed rotation about the nadir (downward) direction. A yaw value of 0 deg indicates that the KMSF +x axis is aligned with the horizontal component of the Earth-relative velocity vector. A yaw value of 180 deg indicates that the spacecraft is in a yaw-flipped state, with the KMSF -x axis aligned with the horizontal component of the Earth-relative velocity vector.
| Bytes |
2.18 MiB |
77.09 kiB |
| Shape |
(286144,) |
(9868,) |
| Dask graph |
29 chunks in 59 graph layers |
| Data type |
float64 numpy.ndarray |
|
 |
velocity_heading
(num_lines)
float64
dask.array<chunksize=(9868,), meta=np.ndarray>

- long_name :
-
heading of the spacecraft Earth-relative velocity vector
- units :
-
degrees
- valid_min :
-
0
- valid_max :
-
359999999
- comment :
-
Angle with respect to true north of the horizontal component of the spacecraft Earth-relative velocity vector. A value of 90 deg indicates that the spacecraft velocity vector pointed due east. Values between 0 and 90 deg indicate that the velocity vector has a northward component, and values between 90 and 180 deg indicate that the velocity vector has a southward component.
| Bytes |
2.18 MiB |
77.09 kiB |
| Shape |
(286144,) |
(9868,) |
| Dask graph |
29 chunks in 59 graph layers |
| Data type |
float64 numpy.ndarray |
|
 |
orbit_qual
(num_lines)
float32
dask.array<chunksize=(9868,), meta=np.ndarray>

- long_name :
-
orbit quality flag
- standard_name :
-
status_flag
- valid_min :
-
0
- valid_max :
-
1
- comment :
-
Orbit quality flag.
| Bytes |
1.09 MiB |
38.55 kiB |
| Shape |
(286144,) |
(9868,) |
| Dask graph |
29 chunks in 59 graph layers |
| Data type |
float32 numpy.ndarray |
|
 |
latitude_avg_ssh
(num_lines, num_pixels)
float64
dask.array<chunksize=(9868, 71), meta=np.ndarray>

- long_name :
-
weighted average latitude of samples used to compute SSH
- standard_name :
-
latitude
- units :
-
degrees_north
- valid_min :
-
-80000000
- valid_max :
-
80000000
- comment :
-
Latitude of measurement [-80,80]. Positive latitude is North latitude, negative latitude is South latitude. This value may be biased away from a nominal grid location if some of the native, unsmoothed samples were discarded during processing.
| Bytes |
155.00 MiB |
5.35 MiB |
| Shape |
(286144, 71) |
(9868, 71) |
| Dask graph |
29 chunks in 59 graph layers |
| Data type |
float64 numpy.ndarray |
|
 |
longitude_avg_ssh
(num_lines, num_pixels)
float64
dask.array<chunksize=(9868, 71), meta=np.ndarray>

- long_name :
-
weighted average longitude of samples used to compute SSH
- standard_name :
-
longitude
- units :
-
degrees_east
- valid_min :
-
0
- valid_max :
-
359999999
- comment :
-
Longitude of measurement. East longitude relative to Greenwich meridian. This value may be biased away from a nominal grid location if some of the native, unsmoothed samples were discarded during processing.
| Bytes |
155.00 MiB |
5.35 MiB |
| Shape |
(286144, 71) |
(9868, 71) |
| Dask graph |
29 chunks in 59 graph layers |
| Data type |
float64 numpy.ndarray |
|
 |
cross_track_distance
(num_lines, num_pixels)
float32
dask.array<chunksize=(9868, 71), meta=np.ndarray>

- long_name :
-
cross track distance
- units :
-
m
- valid_min :
-
-75000.0
- valid_max :
-
75000.0
- comment :
-
Distance of sample from nadir. Negative values indicate the left side of the swath, and positive values indicate the right side of the swath.
| Bytes |
77.50 MiB |
2.67 MiB |
| Shape |
(286144, 71) |
(9868, 71) |
| Dask graph |
29 chunks in 59 graph layers |
| Data type |
float32 numpy.ndarray |
|
 |
x_factor
(num_lines, num_pixels)
float32
dask.array<chunksize=(9868, 71), meta=np.ndarray>

- long_name :
-
radiometric calibration X factor as a composite value for the X factors of the +y and -y channels
- units :
-
1
- valid_min :
-
0.0
- valid_max :
-
1e+20
- comment :
-
Radiometric calibration X factor as a linear power ratio.
| Bytes |
77.50 MiB |
2.67 MiB |
| Shape |
(286144, 71) |
(9868, 71) |
| Dask graph |
29 chunks in 59 graph layers |
| Data type |
float32 numpy.ndarray |
|
 |
sig0_cor_atmos_model
(num_lines, num_pixels)
float32
dask.array<chunksize=(9868, 71), meta=np.ndarray>

- long_name :
-
two-way atmospheric correction to sigma0 from model
- source :
-
European Centre for Medium-Range Weather Forecasts
- institution :
-
ECMWF
- units :
-
1
- valid_min :
-
1.0
- valid_max :
-
10.0
- comment :
-
Atmospheric correction to sigma0 from weather model data as a linear power multiplier (not decibels). sig0_cor_atmos_model is already applied in computing sig0_karin_2.
| Bytes |
77.50 MiB |
2.67 MiB |
| Shape |
(286144, 71) |
(9868, 71) |
| Dask graph |
29 chunks in 59 graph layers |
| Data type |
float32 numpy.ndarray |
|
 |
sig0_cor_atmos_rad
(num_lines, num_pixels)
float32
dask.array<chunksize=(9868, 71), meta=np.ndarray>

- long_name :
-
two-way atmospheric correction to sigma0 from radiometer data
- source :
-
Advanced Microwave Radiometer
- units :
-
1
- valid_min :
-
1.0
- valid_max :
-
10.0
- comment :
-
Atmospheric correction to sigma0 from radiometer data as a linear power multiplier (not decibels). sig0_cor_atmos_rad is already applied in computing sig0_karin.
| Bytes |
77.50 MiB |
2.67 MiB |
| Shape |
(286144, 71) |
(9868, 71) |
| Dask graph |
29 chunks in 59 graph layers |
| Data type |
float32 numpy.ndarray |
|
 |
doppler_centroid
(num_lines, num_sides)
float32
dask.array<chunksize=(9868, 2), meta=np.ndarray>

- long_name :
-
doppler centroid estimated by KaRIn
- units :
-
1/s
- valid_min :
-
-30000
- valid_max :
-
30000
- comment :
-
Doppler centroid (in hertz or cycles per second) estimated by KaRIn.
| Bytes |
2.18 MiB |
77.09 kiB |
| Shape |
(286144, 2) |
(9868, 2) |
| Dask graph |
29 chunks in 59 graph layers |
| Data type |
float32 numpy.ndarray |
|
 |
phase_bias_ref_surface
(num_lines, num_pixels)
float64
dask.array<chunksize=(9868, 71), meta=np.ndarray>

- long_name :
-
height of reference surface used for phase bias calculation
- units :
-
m
- valid_min :
-
-15000000
- valid_max :
-
150000000
- comment :
-
Height (relative to the reference ellipsoid) of the reference surface used for phase bias calculation during L1B processing.
| Bytes |
155.00 MiB |
5.35 MiB |
| Shape |
(286144, 71) |
(9868, 71) |
| Dask graph |
29 chunks in 59 graph layers |
| Data type |
float64 numpy.ndarray |
|
 |
obp_ref_surface
(num_lines, num_pixels)
float64
dask.array<chunksize=(9868, 71), meta=np.ndarray>

- long_name :
-
height of reference surface used by on-board-processor
- units :
-
m
- valid_min :
-
-15000000
- valid_max :
-
150000000
- comment :
-
Height (relative to the reference ellipsoid) of the reference surface used by the KaRIn on-board processor.
| Bytes |
155.00 MiB |
5.35 MiB |
| Shape |
(286144, 71) |
(9868, 71) |
| Dask graph |
29 chunks in 59 graph layers |
| Data type |
float64 numpy.ndarray |
|
 |
rad_tmb_187
(num_lines, num_sides)
float32
dask.array<chunksize=(9868, 2), meta=np.ndarray>

- long_name :
-
radiometer main beam brightness temperature at 18.7 GHz
- standard_name :
-
toa_brightness_temperature
- source :
-
Advanced Microwave Radiometer
- units :
-
K
- valid_min :
-
13000
- valid_max :
-
25000
- comment :
-
Main beam brightness temperature measurement at 18.7 GHz. Value is unsmoothed (along-track averaging has not been performed).
| Bytes |
2.18 MiB |
77.09 kiB |
| Shape |
(286144, 2) |
(9868, 2) |
| Dask graph |
29 chunks in 59 graph layers |
| Data type |
float32 numpy.ndarray |
|
 |
rad_tmb_238
(num_lines, num_sides)
float32
dask.array<chunksize=(9868, 2), meta=np.ndarray>

- long_name :
-
radiometer main beam brightness temperature at 23.8 GHz
- standard_name :
-
toa_brightness_temperature
- source :
-
Advanced Microwave Radiometer
- units :
-
K
- valid_min :
-
13000
- valid_max :
-
25000
- comment :
-
Main beam brightness temperature measurement at 23.8 GHz. Value is unsmoothed (along-track averaging has not been performed).
| Bytes |
2.18 MiB |
77.09 kiB |
| Shape |
(286144, 2) |
(9868, 2) |
| Dask graph |
29 chunks in 59 graph layers |
| Data type |
float32 numpy.ndarray |
|
 |
rad_tmb_340
(num_lines, num_sides)
float32
dask.array<chunksize=(9868, 2), meta=np.ndarray>

- long_name :
-
radiometer main beam brightness temperature at 34.0 GHz
- standard_name :
-
toa_brightness_temperature
- source :
-
Advanced Microwave Radiometer
- units :
-
K
- valid_min :
-
15000
- valid_max :
-
28000
- comment :
-
Main beam brightness temperature measurement at 34.0 GHz. Value is unsmoothed (along-track averaging has not been performed).
| Bytes |
2.18 MiB |
77.09 kiB |
| Shape |
(286144, 2) |
(9868, 2) |
| Dask graph |
29 chunks in 59 graph layers |
| Data type |
float32 numpy.ndarray |
|
 |
rad_water_vapor
(num_lines, num_sides)
float32
dask.array<chunksize=(9868, 2), meta=np.ndarray>

- long_name :
-
water vapor content from radiometer
- standard_name :
-
atmosphere_water_vapor_content
- source :
-
Advanced Microwave Radiometer
- units :
-
kg/m^2
- valid_min :
-
0
- valid_max :
-
15000
- comment :
-
Integrated water vapor content from radiometer measurements.
| Bytes |
2.18 MiB |
77.09 kiB |
| Shape |
(286144, 2) |
(9868, 2) |
| Dask graph |
29 chunks in 59 graph layers |
| Data type |
float32 numpy.ndarray |
|
 |
rad_cloud_liquid_water
(num_lines, num_sides)
float32
dask.array<chunksize=(9868, 2), meta=np.ndarray>

- long_name :
-
liquid water content from radiometer
- standard_name :
-
atmosphere_cloud_liquid_water_content
- source :
-
Advanced Microwave Radiometer
- units :
-
kg/m^2
- valid_min :
-
0
- valid_max :
-
2000
- comment :
-
Integrated cloud liquid water content from radiometer measurements.
| Bytes |
2.18 MiB |
77.09 kiB |
| Shape |
(286144, 2) |
(9868, 2) |
| Dask graph |
29 chunks in 59 graph layers |
| Data type |
float32 numpy.ndarray |
|
 |
mean_sea_surface_cnescls
(num_lines, num_pixels)
float64
dask.array<chunksize=(9868, 71), meta=np.ndarray>

- long_name :
-
mean sea surface height (CNES/CLS)
- source :
-
CNES_CLS_15
- institution :
-
CNES/CLS
- units :
-
m
- valid_min :
-
-1500000
- valid_max :
-
1500000
- comment :
-
Mean sea surface height above the reference ellipsoid. The value is referenced to the mean tide system, i.e. includes the permanent tide (zero frequency).
| Bytes |
155.00 MiB |
5.35 MiB |
| Shape |
(286144, 71) |
(9868, 71) |
| Dask graph |
29 chunks in 59 graph layers |
| Data type |
float64 numpy.ndarray |
|
 |
mean_sea_surface_cnescls_uncert
(num_lines, num_pixels)
float32
dask.array<chunksize=(9868, 71), meta=np.ndarray>

- long_name :
-
mean sea surface height accuracy (CNES/CLS)
- source :
-
CNES_CLS_15
- institution :
-
CNES/CLS
- units :
-
m
- valid_min :
-
0
- valid_max :
-
10000
- comment :
-
Accuracy of the mean sea surface height (mean_sea_surface_cnescls).
| Bytes |
77.50 MiB |
2.67 MiB |
| Shape |
(286144, 71) |
(9868, 71) |
| Dask graph |
29 chunks in 59 graph layers |
| Data type |
float32 numpy.ndarray |
|
 |
mean_sea_surface_dtu
(num_lines, num_pixels)
float64
dask.array<chunksize=(9868, 71), meta=np.ndarray>

- long_name :
-
mean sea surface height (DTU)
- source :
-
DTU18
- institution :
-
DTU
- units :
-
m
- valid_min :
-
-1500000
- valid_max :
-
1500000
- comment :
-
Mean sea surface height above the reference ellipsoid. The value is referenced to the mean tide system, i.e. includes the permanent tide (zero frequency).
| Bytes |
155.00 MiB |
5.35 MiB |
| Shape |
(286144, 71) |
(9868, 71) |
| Dask graph |
29 chunks in 59 graph layers |
| Data type |
float64 numpy.ndarray |
|
 |
mean_sea_surface_dtu_uncert
(num_lines, num_pixels)
float32
dask.array<chunksize=(9868, 71), meta=np.ndarray>

- long_name :
-
mean sea surface height accuracy (DTU)
- source :
-
DTU18
- institution :
-
DTU
- units :
-
m
- valid_min :
-
0
- valid_max :
-
10000
- comment :
-
Accuracy of the mean sea surface height (mean_sea_surface_dtu)
| Bytes |
77.50 MiB |
2.67 MiB |
| Shape |
(286144, 71) |
(9868, 71) |
| Dask graph |
29 chunks in 59 graph layers |
| Data type |
float32 numpy.ndarray |
|
 |
geoid
(num_lines, num_pixels)
float64
dask.array<chunksize=(9868, 71), meta=np.ndarray>

- long_name :
-
geoid height
- standard_name :
-
geoid_height_above_reference_ellipsoid
- source :
-
EGM2008 (Pavlis et al., 2012)
- units :
-
m
- valid_min :
-
-1500000
- valid_max :
-
1500000
- comment :
-
Geoid height above the reference ellipsoid with a correction to refer the value to the mean tide system, i.e. includes the permanent tide (zero frequency).
| Bytes |
155.00 MiB |
5.35 MiB |
| Shape |
(286144, 71) |
(9868, 71) |
| Dask graph |
29 chunks in 59 graph layers |
| Data type |
float64 numpy.ndarray |
|
 |
mean_dynamic_topography
(num_lines, num_pixels)
float32
dask.array<chunksize=(9868, 71), meta=np.ndarray>

- long_name :
-
mean dynamic topography
- source :
-
CNES_CLS_18
- institution :
-
CNES/CLS
- units :
-
m
- valid_min :
-
-30000
- valid_max :
-
30000
- comment :
-
Mean dynamic topography above the geoid.
| Bytes |
77.50 MiB |
2.67 MiB |
| Shape |
(286144, 71) |
(9868, 71) |
| Dask graph |
29 chunks in 59 graph layers |
| Data type |
float32 numpy.ndarray |
|
 |
mean_dynamic_topography_uncert
(num_lines, num_pixels)
float32
dask.array<chunksize=(9868, 71), meta=np.ndarray>

- long_name :
-
mean dynamic topography accuracy
- source :
-
CNES_CLS_18
- institution :
-
CNES/CLS
- units :
-
m
- valid_min :
-
0
- valid_max :
-
10000
- comment :
-
Accuracy of the mean dynamic topography.
| Bytes |
77.50 MiB |
2.67 MiB |
| Shape |
(286144, 71) |
(9868, 71) |
| Dask graph |
29 chunks in 59 graph layers |
| Data type |
float32 numpy.ndarray |
|
 |
depth_or_elevation
(num_lines, num_pixels)
float32
dask.array<chunksize=(9868, 71), meta=np.ndarray>

- long_name :
-
ocean depth or land elevation
- source :
-
Altimeter Corrected Elevations, version 2
- institution :
-
European Space Agency
- units :
-
m
- valid_min :
-
-12000
- valid_max :
-
10000
- comment :
-
Ocean depth or land elevation above reference ellipsoid. Ocean depth (bathymetry) is given as negative values, and land elevation positive values.
| Bytes |
77.50 MiB |
2.67 MiB |
| Shape |
(286144, 71) |
(9868, 71) |
| Dask graph |
29 chunks in 59 graph layers |
| Data type |
float32 numpy.ndarray |
|
 |
solid_earth_tide
(num_lines, num_pixels)
float32
dask.array<chunksize=(9868, 71), meta=np.ndarray>

- long_name :
-
solid Earth tide height
- source :
-
Cartwright and Taylor (1971) and Cartwright and Edden (1973)
- units :
-
m
- valid_min :
-
-10000
- valid_max :
-
10000
- comment :
-
Solid-Earth (body) tide height. The zero-frequency permanent tide component is not included.
| Bytes |
77.50 MiB |
2.67 MiB |
| Shape |
(286144, 71) |
(9868, 71) |
| Dask graph |
29 chunks in 59 graph layers |
| Data type |
float32 numpy.ndarray |
|
 |
ocean_tide_fes
(num_lines, num_pixels)
float64
dask.array<chunksize=(9868, 71), meta=np.ndarray>

- long_name :
-
geocentric ocean tide height (FES)
- source :
-
FES2014b (Carrere et al., 2016)
- institution :
-
LEGOS/CNES
- units :
-
m
- valid_min :
-
-300000
- valid_max :
-
300000
- comment :
-
Geocentric ocean tide height. Includes the sum total of the ocean tide, the corresponding load tide (load_tide_fes) and equilibrium long-period ocean tide height (ocean_tide_eq).
| Bytes |
155.00 MiB |
5.35 MiB |
| Shape |
(286144, 71) |
(9868, 71) |
| Dask graph |
29 chunks in 59 graph layers |
| Data type |
float64 numpy.ndarray |
|
 |
ocean_tide_got
(num_lines, num_pixels)
float64
dask.array<chunksize=(9868, 71), meta=np.ndarray>

- long_name :
-
geocentric ocean tide height (GOT)
- source :
-
GOT4.10c (Ray, 2013)
- institution :
-
GSFC
- units :
-
m
- valid_min :
-
-300000
- valid_max :
-
300000
- comment :
-
Geocentric ocean tide height. Includes the sum total of the ocean tide, the corresponding load tide (load_tide_got) and equilibrium long-period ocean tide height (ocean_tide_eq).
| Bytes |
155.00 MiB |
5.35 MiB |
| Shape |
(286144, 71) |
(9868, 71) |
| Dask graph |
29 chunks in 59 graph layers |
| Data type |
float64 numpy.ndarray |
|
 |
load_tide_fes
(num_lines, num_pixels)
float32
dask.array<chunksize=(9868, 71), meta=np.ndarray>

- long_name :
-
geocentric load tide height (FES)
- source :
-
FES2014b (Carrere et al., 2016)
- institution :
-
LEGOS/CNES
- units :
-
m
- valid_min :
-
-2000
- valid_max :
-
2000
- comment :
-
Geocentric load tide height. The effect of the ocean tide loading of the Earth's crust. This value has already been added to the corresponding ocean tide height value (ocean_tide_fes).
| Bytes |
77.50 MiB |
2.67 MiB |
| Shape |
(286144, 71) |
(9868, 71) |
| Dask graph |
29 chunks in 59 graph layers |
| Data type |
float32 numpy.ndarray |
|
 |
load_tide_got
(num_lines, num_pixels)
float32
dask.array<chunksize=(9868, 71), meta=np.ndarray>

- long_name :
-
geocentric load tide height (GOT)
- source :
-
GOT4.10c (Ray, 2013)
- institution :
-
GSFC
- units :
-
m
- valid_min :
-
-2000
- valid_max :
-
2000
- comment :
-
Geocentric load tide height. The effect of the ocean tide loading of the Earth's crust. This value has already been added to the corresponding ocean tide height value (ocean_tide_got).
| Bytes |
77.50 MiB |
2.67 MiB |
| Shape |
(286144, 71) |
(9868, 71) |
| Dask graph |
29 chunks in 59 graph layers |
| Data type |
float32 numpy.ndarray |
|
 |
ocean_tide_eq
(num_lines, num_pixels)
float32
dask.array<chunksize=(9868, 71), meta=np.ndarray>

- long_name :
-
equilibrium long-period ocean tide height
- units :
-
m
- valid_min :
-
-2000
- valid_max :
-
2000
- comment :
-
Equilibrium long-period ocean tide height. This value has already been added to the corresponding ocean tide height values (ocean_tide_fes and ocean_tide_got).
| Bytes |
77.50 MiB |
2.67 MiB |
| Shape |
(286144, 71) |
(9868, 71) |
| Dask graph |
29 chunks in 59 graph layers |
| Data type |
float32 numpy.ndarray |
|
 |
ocean_tide_non_eq
(num_lines, num_pixels)
float32
dask.array<chunksize=(9868, 71), meta=np.ndarray>

- long_name :
-
non-equilibrium long-period ocean tide height
- source :
-
FES2014b (Carrere et al., 2016)
- institution :
-
LEGOS/CNES
- units :
-
m
- valid_min :
-
-2000
- valid_max :
-
2000
- comment :
-
Non-equilibrium long-period ocean tide height. This value is reported as a relative displacement with repsect to ocean_tide_eq. This value can be added to ocean_tide_eq, ocean_tide_fes, or ocean_tide_got, or subtracted from ssha_karin and ssha_karin_2, to account for the total long-period ocean tides from equilibrium and non-equilibrium contributions.
| Bytes |
77.50 MiB |
2.67 MiB |
| Shape |
(286144, 71) |
(9868, 71) |
| Dask graph |
29 chunks in 59 graph layers |
| Data type |
float32 numpy.ndarray |
|
 |
internal_tide_hret
(num_lines, num_pixels)
float32
dask.array<chunksize=(9868, 71), meta=np.ndarray>

- long_name :
-
coherent internal tide (HRET)
- source :
-
Zaron (2019)
- units :
-
m
- valid_min :
-
-2000
- valid_max :
-
2000
- comment :
-
Coherent internal ocean tide. This value is subtracted from the ssh_karin and ssh_karin_2 to compute ssha_karin and ssha_karin_2, respectively.
| Bytes |
77.50 MiB |
2.67 MiB |
| Shape |
(286144, 71) |
(9868, 71) |
| Dask graph |
29 chunks in 59 graph layers |
| Data type |
float32 numpy.ndarray |
|
 |
internal_tide_sol2
(num_lines, num_pixels)
float32
dask.array<chunksize=(9868, 71), meta=np.ndarray>

- long_name :
-
coherent internal tide (Model 2)
- source :
-
TBD
- units :
-
m
- valid_min :
-
-2000
- valid_max :
-
2000
- comment :
-
Coherent internal tide.
| Bytes |
77.50 MiB |
2.67 MiB |
| Shape |
(286144, 71) |
(9868, 71) |
| Dask graph |
29 chunks in 59 graph layers |
| Data type |
float32 numpy.ndarray |
|
 |
pole_tide
(num_lines, num_pixels)
float32
dask.array<chunksize=(9868, 71), meta=np.ndarray>

- long_name :
-
geocentric pole tide height
- source :
-
Wahr (1985) and Desai et al. (2015)
- units :
-
m
- valid_min :
-
-2000
- valid_max :
-
2000
- comment :
-
Geocentric pole tide height. The total of the contribution from the solid-Earth (body) pole tide height, the ocean pole tide height, and the load pole tide height (i.e., the effect of the ocean pole tide loading of the Earth's crust).
| Bytes |
77.50 MiB |
2.67 MiB |
| Shape |
(286144, 71) |
(9868, 71) |
| Dask graph |
29 chunks in 59 graph layers |
| Data type |
float32 numpy.ndarray |
|
 |
dac
(num_lines, num_pixels)
float32
dask.array<chunksize=(9868, 71), meta=np.ndarray>

- long_name :
-
dynamic atmospheric correction
- source :
-
MOG2D
- institution :
-
LEGOS/CNES/CLS
- units :
-
m
- valid_min :
-
-12000
- valid_max :
-
12000
- comment :
-
Model estimate of the effect on sea surface topography due to high frequency air pressure and wind effects and the low-frequency height from inverted barometer effect (inv_bar_cor). This value is subtracted from the ssh_karin and ssh_karin_2 to compute ssha_karin and ssha_karin_2, respectively. Use only one of inv_bar_cor and dac.
| Bytes |
77.50 MiB |
2.67 MiB |
| Shape |
(286144, 71) |
(9868, 71) |
| Dask graph |
29 chunks in 59 graph layers |
| Data type |
float32 numpy.ndarray |
|
 |
inv_bar_cor
(num_lines, num_pixels)
float32
dask.array<chunksize=(9868, 71), meta=np.ndarray>

- long_name :
-
static inverse barometer effect on sea surface height
- units :
-
m
- valid_min :
-
-2000
- valid_max :
-
2000
- comment :
-
Estimate of static effect of atmospheric pressure on sea surface height. Above average pressure lowers sea surface height. Computed by interpolating ECMWF pressure fields in space and time. The value is included in dac. To apply, add dac to ssha_karin and ssha_karin_2 and subtract inv_bar_cor.
| Bytes |
77.50 MiB |
2.67 MiB |
| Shape |
(286144, 71) |
(9868, 71) |
| Dask graph |
29 chunks in 59 graph layers |
| Data type |
float32 numpy.ndarray |
|
 |
model_dry_tropo_cor
(num_lines, num_pixels)
float32
dask.array<chunksize=(9868, 71), meta=np.ndarray>

- long_name :
-
dry troposphere vertical correction
- source :
-
European Centre for Medium-Range Weather Forecasts
- institution :
-
ECMWF
- units :
-
m
- valid_min :
-
-30000
- valid_max :
-
-15000
- comment :
-
Equivalent vertical correction due to dry troposphere delay. The reported sea surface height, latitude and longitude are computed after adding negative media corrections to uncorrected range along slant-range paths, accounting for the differential delay between the two KaRIn antennas. The equivalent vertical correction is computed by applying obliquity factors to the slant-path correction. Adding the reported correction to the reported sea surface height results in the uncorrected sea surface height.
| Bytes |
77.50 MiB |
2.67 MiB |
| Shape |
(286144, 71) |
(9868, 71) |
| Dask graph |
29 chunks in 59 graph layers |
| Data type |
float32 numpy.ndarray |
|
 |
model_wet_tropo_cor
(num_lines, num_pixels)
float32
dask.array<chunksize=(9868, 71), meta=np.ndarray>

- long_name :
-
wet troposphere vertical correction from weather model data
- source :
-
European Centre for Medium-Range Weather Forecasts
- institution :
-
ECMWF
- units :
-
m
- valid_min :
-
-10000
- valid_max :
-
0
- comment :
-
Equivalent vertical correction due to wet troposphere delay from weather model data. The reported pixel height, latitude and longitude are computed after adding negative media corrections to uncorrected range along slant-range paths, accounting for the differential delay between the two KaRIn antennas. The equivalent vertical correction is computed by applying obliquity factors to the slant-path correction. Adding the reported correction to the reported sea surface height (ssh_karin_2) results in the uncorrected sea surface height.
| Bytes |
77.50 MiB |
2.67 MiB |
| Shape |
(286144, 71) |
(9868, 71) |
| Dask graph |
29 chunks in 59 graph layers |
| Data type |
float32 numpy.ndarray |
|
 |
rad_wet_tropo_cor
(num_lines, num_pixels)
float32
dask.array<chunksize=(9868, 71), meta=np.ndarray>

- long_name :
-
wet troposphere vertical correction from radiometer data
- source :
-
Advanced Microwave Radiometer
- units :
-
m
- valid_min :
-
-10000
- valid_max :
-
0
- comment :
-
Equivalent vertical correction due to wet troposphere delay from radiometer measurements. The reported pixel height, latitude and longitude are computed after adding negative media corrections to uncorrected range along slant-range paths, accounting for the differential delay between the two KaRIn antennas. The equivalent vertical correction is computed by applying obliquity factors to the slant-path correction. Adding the reported correction to the reported sea surface height (ssh_karin) results in the uncorrected sea surface height.
| Bytes |
77.50 MiB |
2.67 MiB |
| Shape |
(286144, 71) |
(9868, 71) |
| Dask graph |
29 chunks in 59 graph layers |
| Data type |
float32 numpy.ndarray |
|
 |
iono_cor_gim_ka
(num_lines, num_pixels)
float32
dask.array<chunksize=(9868, 71), meta=np.ndarray>

- long_name :
-
ionosphere vertical correction
- source :
-
Global Ionosphere Maps
- institution :
-
JPL
- units :
-
m
- valid_min :
-
-5000
- valid_max :
-
0
- comment :
-
Equivalent vertical correction due to ionosphere delay. The reported sea surface height, latitude and longitude are computed after adding negative media corrections to uncorrected range along slant-range paths, accounting for the differential delay between the two KaRIn antennas. The equivalent vertical correction is computed by applying obliquity factors to the slant-path correction. Adding the reported correction to the reported sea surface height results in the uncorrected sea surface height.
| Bytes |
77.50 MiB |
2.67 MiB |
| Shape |
(286144, 71) |
(9868, 71) |
| Dask graph |
29 chunks in 59 graph layers |
| Data type |
float32 numpy.ndarray |
|
 |
height_cor_xover
(num_lines, num_pixels)
float64
dask.array<chunksize=(9868, 71), meta=np.ndarray>

- long_name :
-
height correction from KaRIn crossovers
- units :
-
m
- valid_min :
-
-100000
- valid_max :
-
100000
- comment :
-
Height correction from KaRIn crossover calibration. To apply this correction the value of height_cor_xover should be added to the value of ssh_karin, ssh_karin_2, ssha_karin, and ssha_karin_2.
| Bytes |
155.00 MiB |
5.35 MiB |
| Shape |
(286144, 71) |
(9868, 71) |
| Dask graph |
29 chunks in 59 graph layers |
| Data type |
float64 numpy.ndarray |
|
 |
correction_flag
(num_lines, num_pixels)
float32
dask.array<chunksize=(9868, 71), meta=np.ndarray>

- long_name :
-
quality flag for corrections
- standard_name :
-
status_flag
- flag_meanings :
-
good bad
- flag_values :
-
[0 1]
- valid_min :
-
0
- valid_max :
-
1
- comment :
-
Quality flag for corrections.
| Bytes |
77.50 MiB |
2.67 MiB |
| Shape |
(286144, 71) |
(9868, 71) |
| Dask graph |
29 chunks in 59 graph layers |
| Data type |
float32 numpy.ndarray |
|
 |
rain_rate
(num_lines, num_pixels)
float32
dask.array<chunksize=(9868, 71), meta=np.ndarray>

- long_name :
-
rain rate from weather model
- source :
-
European Centre for Medium-Range Weather Forecasts
- institution :
-
ECMWF
- units :
-
mm/hr
- valid_min :
-
0
- valid_max :
-
200
- comment :
-
Rain rate from weather model.
| Bytes |
77.50 MiB |
2.67 MiB |
| Shape |
(286144, 71) |
(9868, 71) |
| Dask graph |
29 chunks in 59 graph layers |
| Data type |
float32 numpy.ndarray |
|
 |
ice_conc
(num_lines, num_pixels)
float32
dask.array<chunksize=(9868, 71), meta=np.ndarray>

- long_name :
-
concentration of sea ice
- standard_name :
-
sea_ice_area_fraction
- source :
-
EUMETSAT Ocean and Sea Ice Satellite Applications Facility
- institution :
-
EUMETSAT
- units :
-
%
- valid_min :
-
0
- valid_max :
-
10000
- comment :
-
Concentration of sea ice from model.
| Bytes |
77.50 MiB |
2.67 MiB |
| Shape |
(286144, 71) |
(9868, 71) |
| Dask graph |
29 chunks in 59 graph layers |
| Data type |
float32 numpy.ndarray |
|
 |
sea_state_bias_cor
(num_lines, num_pixels)
float32
dask.array<chunksize=(9868, 71), meta=np.ndarray>

- long_name :
-
sea state bias correction to height
- source :
-
TBD
- units :
-
m
- valid_min :
-
-6000
- valid_max :
-
0
- comment :
-
Sea state bias correction to ssh_karin. Adding the reported correction to the reported sea surface height results in the uncorrected sea surface height. The wind_speed_karin value is used to compute this quantity.
| Bytes |
77.50 MiB |
2.67 MiB |
| Shape |
(286144, 71) |
(9868, 71) |
| Dask graph |
29 chunks in 59 graph layers |
| Data type |
float32 numpy.ndarray |
|
 |
sea_state_bias_cor_2
(num_lines, num_pixels)
float32
dask.array<chunksize=(9868, 71), meta=np.ndarray>

- long_name :
-
sea state bias correction to height
- source :
-
TBD
- units :
-
m
- valid_min :
-
-6000
- valid_max :
-
0
- comment :
-
Sea state bias correction to ssh_karin_2. Adding the reported correction to the reported sea surface height results in the uncorrected sea surface height. The wind_speed_karin_2 value is used to compute this quantity.
| Bytes |
77.50 MiB |
2.67 MiB |
| Shape |
(286144, 71) |
(9868, 71) |
| Dask graph |
29 chunks in 59 graph layers |
| Data type |
float32 numpy.ndarray |
|
 |
swh_sea_state_bias
(num_lines, num_pixels)
float32
dask.array<chunksize=(9868, 71), meta=np.ndarray>

- long_name :
-
SWH used in sea state bias correction
- units :
-
m
- valid_min :
-
0
- valid_max :
-
25000
- comment :
-
Significant wave height used in sea state bias correction.
| Bytes |
77.50 MiB |
2.67 MiB |
| Shape |
(286144, 71) |
(9868, 71) |
| Dask graph |
29 chunks in 59 graph layers |
| Data type |
float32 numpy.ndarray |
|
 |
simulated_true_ssh_karin
(num_lines, num_pixels)
float64
dask.array<chunksize=(9868, 71), meta=np.ndarray>

- long_name :
-
sea surface height
- standard_name :
-
sea surface height above reference ellipsoid
- units :
-
m
- valid_min :
-
-15000000
- valid_max :
-
150000000
- comment :
-
Height of the sea surface free of measurement errors.
| Bytes |
155.00 MiB |
5.35 MiB |
| Shape |
(286144, 71) |
(9868, 71) |
| Dask graph |
29 chunks in 59 graph layers |
| Data type |
float64 numpy.ndarray |
|
 |
simulated_error_karin
(num_lines, num_pixels)
float64
dask.array<chunksize=(9868, 71), meta=np.ndarray>

- long_name :
-
KaRIn error
- units :
-
m
| Bytes |
155.00 MiB |
5.35 MiB |
| Shape |
(286144, 71) |
(9868, 71) |
| Dask graph |
29 chunks in 59 graph layers |
| Data type |
float64 numpy.ndarray |
|
 |
simulated_error_timing
(num_lines, num_pixels)
float64
dask.array<chunksize=(9868, 71), meta=np.ndarray>

- long_name :
-
Timing error
- units :
-
m
| Bytes |
155.00 MiB |
5.35 MiB |
| Shape |
(286144, 71) |
(9868, 71) |
| Dask graph |
29 chunks in 59 graph layers |
| Data type |
float64 numpy.ndarray |
|
 |
simulated_error_baseline_dilation
(num_lines, num_pixels)
float64
dask.array<chunksize=(9868, 71), meta=np.ndarray>

- long_name :
-
Error due to baseline mast dilation
- units :
-
m
| Bytes |
155.00 MiB |
5.35 MiB |
| Shape |
(286144, 71) |
(9868, 71) |
| Dask graph |
29 chunks in 59 graph layers |
| Data type |
float64 numpy.ndarray |
|
 |
simulated_error_roll
(num_lines, num_pixels)
float64
dask.array<chunksize=(9868, 71), meta=np.ndarray>

- long_name :
-
Error due to roll
- units :
-
m
| Bytes |
155.00 MiB |
5.35 MiB |
| Shape |
(286144, 71) |
(9868, 71) |
| Dask graph |
29 chunks in 59 graph layers |
| Data type |
float64 numpy.ndarray |
|
 |
simulated_error_phase
(num_lines, num_pixels)
float64
dask.array<chunksize=(9868, 71), meta=np.ndarray>

- long_name :
-
Error due to phase
- units :
-
m
| Bytes |
155.00 MiB |
5.35 MiB |
| Shape |
(286144, 71) |
(9868, 71) |
| Dask graph |
29 chunks in 59 graph layers |
| Data type |
float64 numpy.ndarray |
|
 |
simulated_error_orbital
(num_lines, num_pixels)
float64
dask.array<chunksize=(9868, 71), meta=np.ndarray>

- long_name :
-
Error due to orbital perturbations
- units :
-
m
| Bytes |
155.00 MiB |
5.35 MiB |
| Shape |
(286144, 71) |
(9868, 71) |
| Dask graph |
29 chunks in 59 graph layers |
| Data type |
float64 numpy.ndarray |
|
 |